The Hidden Influence of Socioeconomic Differences on Elementary Students' Help-Seeking Networks and Mathematics Performance

Abstract

In a world where collaborative learning and social interactions play pivotal roles in educational success, this study explores the dynamics of elementary students’ help-seeking behaviors in mathematics education. Employing Social Network Analysis (SNA), regression models, and comprehensive statistical analyses, the study explores the association between students’ mathematics help-seeking networks and their performance, while also examining the potential moderating effect of socioeconomic status (SES). Furthermore, the study investigates the influence of SES on students’ selection of helpers when facing academic challenges in mathematics. The findings reveal a positive association between students’ mathematics help-seeking indegree centrality—indicative of being nominated as a helper—and their performance. Conversely, a negative association is observed between mathematics help-seeking outdegree centrality—reflective of seeking help from others—and performance. However, these associations were not found to be significantly moderated by SES. Instead, SES influences the choice of helper sources, demonstrating a disparity in access to educational support. Students from wealthier backgrounds tend to rely on outside-of-school resources such as parental support and private tutoring to a greater extent than expected from a random sample, while students from less affluent backgrounds depend more on within-school resources, such as teachers and peers. The study emphasizes the importance of cultivating classroom cultures that value constructive help-seeking, which is integral to enhancing understanding and creating collaborative learning environments. Additionally, the study sheds light on educational inequalities linked to cultural capital, particularly concerning the accessibility of help resources. To address these disparities, strategies such as parental engagement workshops and the development of comprehensive digital platforms are recommended to promote equitable access to assistance across socioeconomic spectrums. Moreover, the potential of Artificial Intelligence in education is noted as a promising tool for providing personalized student support, capable of bridging socioeconomic and cultural gaps. This research concludes with a call to action for educators, policymakers, and community stakeholders to establish educational environments that encourage help-seeking as an effective learning strategy and support equitable access to resources. Such initiatives are crucial for promoting equal opportunities for educational resources and empowering every student to reach their full potential.